Charles Chase is the executive industry consultant and trusted advisor for the SAS Retail/CPG global practice. He is the author of Next Generation Demand Management: People, Process, Analytics and Technology, author of Demand-Driven Forecasting: A Structured Approach to Forecasting, and co-author of Bricks Matter: The Role of Supply Chains in Building Market-Driven Differentiation, as well as over 50 articles in several business journals on demand forecasting and planning, supply chain management, and market response modeling. His latest book is Consumption-Based Forecasting and Planning: Predicting Changing Demand Patterns in the New Digital Economy. To learn more, please see his Author page.
The real reason companies cleanse the historical demand is that traditional forecasting solutions were unable to predict sales promotions or correct the data automatically for shortages, or outliers. To address the short comings of traditional technology, companies embedded a cleansing process of adjusting the demand history for shortages, outliers, and
With all the enhancements in demand management over the past decade, companies are still faced with challenges impeding the advancement of demand-driven planning. Many organizations are struggling with how to analyze and make practical use of the mass of data being collected and stored. Others are perplexed as how to
I was recently asked by a customer if they should move the responsibility for creating the statistical baseline forecast. They were considering moving it from their regional country offices to their global headquarters. In addtion, they were considering changing the role of their regional demand planners to only make adjustments to
